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Table of Contents
1 Cover
2 Preface to the Second Edition
3 Preface to the First Edition
6 Part I: The R Language 1 Basics of R 1.1 What Is R? 1.2 Installing R 1.3 R Documentation 1.4 Basics 1.5 Getting Help 1.6 Data Entry 1.7 Missing Values 1.8 Editing 1.9 Tidying Up 1.10 Saving and Retrieving 1.11 Packages 1.12 Interfaces 1.13 Project Reference 2 Summarizing Statistical Data 2.1 Measures of Central Tendency 2.2 Measures of Dispersion 2.3 Overall Summary Statistics 2.4 Programming in R 2.5 Project 3 Graphical Displays 3.1 BOXPLOTS 3.2 HISTOGRAMS 3.3 STEM AND LEAF 3.4 SCATTER PLOTS 3.5 THE LINE OF BEST FIT 3.6 MACHINE LEARNING AND THE LINE OF BEST FIT 3.7 GRAPHICAL DISPLAYS VERSUS SUMMARY STATISTICS 3.8 Projects References
7 Part II: Fundamentals of Probability 4 Probability Basics 4.1 Experiments, Sample Spaces, and Events 4.2 Classical Approach to Probability 4.3 Permutations and Combinations 4.4 The Birthday Problem 4.5 Balls and Bins 4.6 R Functions for Allocation 4.7 Allocation Overload 4.8 Relative Frequency Approach to Probability 4.9 Simulating Probabilities 4.10 Projects Recommended Reading 5 Rules of Probability 5.1 Probability and Sets 5.2 Mutually Exclusive Events 5.3 Complementary Events 5.4 Axioms of Probability 5.5 Properties of Probability Supplementary Reading 6 Conditional Probability 6.1 Multiplication Law of Probability 6.2 Independent Events 6.3 Independence of More than Two Events 6.4 The Intel FIASCO 6.5 Law of Total Probability 6.6 Trees 6.7 Project Note 7 Posterior Probability and Bayes 7.1 Bayes' Rule 7.2 Hardware Fault Diagnosis 7.3 Machine Learning and Classification 7.4 Spam Filtering 7.5 Machine Translation Reference 8 Reliability 8.1 Series Systems 8.2
